Seasonal contribution of assessed sources to submicron and fine particulate matter in a Central European urban area

Source apportionment of suspended particulate matter (PM1, PM2.5 and PM10) collected in road and tram tunnels in Krakow, Poland

Here, we present the results of a comprehensive study of air quality in two tunnels located in the city of Krakow, southern Poland. The study comprised three PM fractions of suspended particulate matter (PM1, PM2.5 and PM10) sampled during campaigns lasting from March 14 to April 24, 2016 and from June 28 to July 18, 2016, in the road tunnel and the tram tunnel, respectively. The collected samples had undergone comprehensive chemical, elemental and carbon isotope analyses. The results of these analyses gave the basis for better characterization of urban transport as a source of air pollution in the city. The concentrations of particulate matter varied, depending on the analysed PM fraction and the place of sampling. For the tram tunnel, the average concentrations were 53.2 µg·m-3 (PM1), 73.8 µg·m-3 (PM2.5), 96.5 µg·m-3 (PM10), to be compared with 44.2 µg·m-3, 137.7 µg·m-3, 221.5 µg·m-3, respectively, recorded in the road tunnel. The isotope-mass balance calculations carried out separately for the road and tram tunnel and for each PM fraction, revealed that 60 to 79% of carbon present in the samples collected in the road tunnel was associated with road transport, to be compared with 15-33% obtained in the tram tunnel. The second in importance were biogenic emissions (17-21% and 41-49% in the road and tram tunnel, respectively. Sixteen different polycyclic aromatic hydrocarbons (PAHs) have been identified in the analysed samples. As expected, much higher concentrations of PAHs were detected in the road tunnel when compared to the tram tunnel. Based on the analysed PAHs concentrations, health risk assessment was determined using 3 different types of indicators: carcinogenic equivalent (CEQ), mutagenic equivalent (MEQ) and toxic equivalent (TEQ).

Short-term exposure to reduced specific-size ambient particulate matter increase the risk of cause-specific cardiovascular disease: A national-wide evidence from hospital admissions

Evidence for the health effects of ambient PM1 (particulate matter with an aerodynamic diameter ≤ 1 µm) pollution is limited, and it remains unclear whether a smaller particulate matter has a greater impact on human health. We conducted a time-series study in 184 major cities by extracting daily hospital data on admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and stroke between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. City-specific associations were estimated with over-dispersed generalized additive models. A random-effects meta-analysis was used to estimate regional and national average associations. We conducted stratified and meta-regression analyses to explore potential effect modifiers of the association. We recorded 8.83 million cardiovascular admissions during the study period. At the national-average level, a 10-μg/m3 increase in same-day PM1, PM2.5(particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10(particulate matter with an aerodynamic diameter ≤ 10 µm) concentrations corresponded to a 1.14% (95% confidence interval 0.88-1.41%), 0.55% (0.40-0.70%), and 0.45% (0.36-0.55%) increase in cardiovascular admissions, respectively. PM1 exposure was also positively associated with all cardiovascular disease subtypes, including ischemic heart disease (1.28% change; 0.99-1.56%), heart failure (1.30% change; 0.70-1.91%), heart rhythm disturbances (1.11% change; 0.65-1.58%), and ischemic stroke (1.29% change; 0.88-1.71%). The associations between PM1 and cardiovascular admissions were stronger in cities with lower PM1 levels, higher air temperatures and relative humidity, as well as in subgroups with elder age (all P < 0.05). This study provides robust evidence of short-term associations between PM1 concentrations and increased hospital admissions for all major cardiovascular diseases in China. Our findings suggest a greater short-term impact on cardiovascular risk from PM1 in comparison to PM2.5 and PM10.

Spatial and Temporal Volatility of PM2.5, PM10 and PM10-Bound B[a]P Concentrations and Assessment of the Exposure of the Population of Silesia in 2018-2021

Air pollution both indoors and outdoors is a major cause of various diseases and premature deaths. Negative health effects are more frequently observed in a number of European countries characterized by significant pollution. In Poland, especially in Upper Silesia, the most serious problem is the high concentration of particulate matter (PM) and PM10-bound benzo[a]pyrene (B[a]P). The main source of these two pollutants is so-called "low emissions" associated with the burning of solid fuels mainly in domestic boilers and liquid fuels in road traffic. This study examined the variability in the PM and PM10-bound B[a]P concentrations and their relationships with meteorological parameters, i.e., atmospheric pressure, air temperature and wind speed, in 2018-2021 at 11 monitoring stations. In many Silesian cities, the average annual concentrations of PM10, PM2.5 and B[a]P were much higher than those recorded in other European countries. At each station, the average daily PM10 concentrations were exceeded on 12 to 126 days a year. Taking into account the WHO recommendation for PM2.5, the highest recorded average daily concentration exceeded the permissible level by almost 40 times. The same relationships were observed in all measurement years: PM10 concentrations were negatively correlated with air temperature (R = -0.386) and wind speed (R = -0.614). The highest concentrations were observed in the temperature range from -15 °C to -5 °C, when the wind speed did not exceed 0.5 m·s^-1. The calculated lifetime cancer risk (LCR) associated with the exposure to B[a]P in the Silesian Voivodeship suggested 30-429 cases per 1 million people in the heating season depending on the scenario used for the calculations (IRIS, EPA or WHO).

Comparison of concentrations of chemical species and emission sources PM2.5 before pandemic and during pandemic in Krakow, Poland

Observations of air pollution in Krakow have shown that air quality has been improved during the last decade. In the presented study two factors affecting the physicochemical characteristic of PM_2.5 fraction at AGH station in Krakow were observed. One is the ban of using solid fuels for heating purposes and the second is COVID-19 pandemic in Krakow. The PM_2.5 fraction was collected during the whole year every 3rd day between 2nd March 2020 and 28th February 2021 at AGH station in Krakow. In total 110 PM_2.5 fraction samples were collected. The chemical composition was determined for these samples. The elemental analysis was performed by energy dispersive X-ray fluorescence (EDXRF) technique, ions analysis was performed by ion chromatography (IC) and black carbon by optical method. In order to identify the emission sources the positive matrix factorization (PMF) was used. The results of such study were compared to similar analysis performed for PM_2.5 for the period from June 2018 to May 2019 at AGH station in Krakow. The PM_2.5 concentration dropped by 25% in 2020/2021 in comparison to 2018/2019 at this station. The concentrations of Si, K, Fe, Zn and Pb were lowering by 43-64% in the year 2020/2021 in comparison to 2018/2019. Cu, Mn, Zn and Pb come from mechanical abrasion of brakes and tires while Ti, Fe, Mn and Si are crustal species. They are the indicators of road dust (non-exhaust traffic source). Moreover, the annual average contribution of traffic/industrial/soil/construction work source was reduced in 2020/2021 in comparison to 2018/2019. As well the annual average contribution of fuels combustion was declining by 22% in 2020/2021 in comparison to 2018/2019. This study shows that the ban and lockdown, during COVID-19 pandemic, had significant impact on the characteristic of air pollution in Krakow.

Locally weighted total least-squares variance component estimation for modeling urban air pollution

Land use regression (LUR) models are one of the standard methods for estimating air pollution concentration in urban areas. These models are usually low accurate due to inappropriate stochastic models (weight matrix). Furthermore, the measurement or modeling of dependent and independent variables used in LUR models is affected by various errors, which indicates the need to use an efficient stochastic and functional model to achieve the best estimation. This study proposes a locally weighted total least-squares variance component estimation (LW-TLS-VCE) for modeling urban air pollution. In the proposed method, in the first step, a locally weighted total least-squares (LW-TLS) regression is developed to simultaneously considers the non-stationary effects and errors of dependent and independent variables. In the second step, the variance components of the stochastic model are estimated to achieve the best linear unbiased estimation of unknowns. The efficiency of the proposed method is evaluated by modeling PM_2.5 concentrations via meteorological, land use, and traffic variables in Isfahan, Iran. The benefits provided by the proposed method, including considering non-stationary effects and random errors of all variables, besides estimating the actual variance of observations, are evaluated by comparing four consecutive methods. The obtained results demonstrate that using a suitable stochastic and functional model will significantly increase the proposed method's efficiency in PM_2.5 modeling.

Ambient concentrations and dosimetry of inhaled size-segregated particulate matter during periods of low urban mobility in Bragança, Portugal

The restrictive measures in place during the COVID-19 pandemic provided a timely scenario to investigate the effects of human activities on air quality, and the extent to which mobility reduction strategies can impact atmospheric pollutant levels. Real-time concentrations of PM₁, PM_2.5 and PM₁₀ were measured using a mobile platform in a small city of Portugal, during morning and afternoon rush hours, in two distinct phases of the pandemic: emergency phase (cold period, lockdown) and calamity phase (warm period, less restricted). The Multiple-Path Particle Dosimetry Model (MPPD) was used to calculate the PM deposition for adults. Large spatio-temporal variabilities and pronounced changes in mean PM concentrations were observed, with lower concentrations in the calamity phase: PM₁ = 2.33 ± 1.61 μg m^-3; PM_2.5 = 5.15 ± 2.77 μg m^-3; PM₁₀ = 23.30 ± 21.53 μg m^-3 than in the emergency phase: PM₁ = 16.85 ± 31.80 μg m^-3; PM_2.5 = 30.92 ± 31.93 μg m^-3; PM₁₀ = 111.27 ± 104.53 μg m^-3. These changes are explained by a combination of meteorological factors and local emissions, mainly residential firewood burning. Regarding regional deposition, PM₁ was the main contributor to deposition in the tracheobronchial (5%) and pulmonary (12%) regions, and PM₁₀ in the head region (92%). In general, total deposition doses were higher for males than for females. This work quantitatively demonstrated that even with a 38% reduction in urban mobility during the lockdown, the use of firewood for residential heating is the main contributor to the high concentrations of PM and the respective inhaled dose.

The global burden of disease attributable to ambient fine particulate matter in 204 countries and territories, 1990-2019: A systematic analysis of the Global Burden of Disease Study 2019

Understanding the spatio-temporal patterns of the disease burden attributable to ambient PM2.5 across the world is essential for the prevention of related diseases, as well as ambient PM2.5 control. Following the framework and methodology of the Global Burden of Disease Study (GBD) in 2019, the global, regional, and national data on ambient PM2.5-attributable death and disability-adjusted life years (DALYs), and the age-standardized rates of mortality (ASMR) and disability-adjusted life years (ASDR) were summarized based on age, gender, year, location and specific diseases. We calculated the average annual percentage change (AAPC) to depict the secular trends of ASMR and ASDR from 1990 to 2019. In 2019, the global ambient PM2.5-related deaths and DALYs were 4,140,970 and 118.2 million, respectively, with 1,702,150 deaths and 47.5 million DALYs for females and 2,438,820 deaths and 70.7 million DALYs for male. In the 13 level-three causes, ischemic heart disease, stroke, chronic obstructive and pulmonary disease (COPD) were the leading three causes of deaths and DALYs attributable to ambient PM2.5. The number of global deaths and DALYs attributable to ambient PM2.5 has increased by 102.3% and 67.7% from 1990 to 2019, respectively. However, ASMR and ASDR showed little change. In the 13 level-three diseases, ischemic heart disease, stroke, COPD, diabetes mellitus, and lung cancer were the top five contributors to the increase of global deaths or DALYs, among which diabetes mellitus had the fastest increase of ASMR and ASDR, with AAPC of 1.5 (95% CI: 1.43, 1.58) and 2.21 (95% CI: 2.15, 2.27), respectively. The population attributable fractions (PAF) of causes in ASMR or ASDR varied significantly across regions, of which PAF of COPD, stroke and lung cancer were the top three. Regarding the GBD region, high PAF mainly occurred in North Africa and Middle East, South Asia, and East Asia. The age-specific PAFs of ischemic heart disease and stroke deaths and DALYs due to ambient PM2.5 were negatively correlated with age. ASMR and ASDR of overall PM2.5 related-burden showed an inverted "V/U" relationship with the socio-demographic index (SDI). The AAPC of ASMR and ASDR of the overall causes showed a strong negative correlation with SDI in 2019, especially at the SDI larger than 0.5. The deaths and DALYs attributable to ambient PM2.5 continued to increase under the context of population growth and aging. Decision-makers should consider controlling the PM2.5 emission when developing the economy.

Estimating changes in air pollutant levels due to COVID-19 lockdown measures based on a business-as-usual prediction scenario using data mining models: A case-study for urban traffic sites in Spain

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO₂, O₃, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013-2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013-2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NO_x, with the largest reduction in the lockdown period above -50%, whereas the increase observed for O₃ contrasts with the NO_x patterns with a maximum increase of 23.9%. The slight reduction in PM10 (-4.1%) and PM2.5 levels (-2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.

Estimating changes in air pollutant levels due to COVID-19 lockdown measures based on a business-as-usual prediction scenario using data mining models: A case-study for urban traffic sites in Spain

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO₂, O₃, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013-2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013-2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NO_x, with the largest reduction in the lockdown period above -50%, whereas the increase observed for O₃ contrasts with the NO_x patterns with a maximum increase of 23.9%. The slight reduction in PM10 (-4.1%) and PM2.5 levels (-2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.

Pollution from Transport: Detection of Tyre Particles in Environmental Samples

Transport is one of the most important sources of environmental pollution. More and more information has shown that one of the greatest sources of emissions from transport are emissions related to the release of microplastics from tyres. This is one of the most underestimated sources of emissions into the environment. In this study, environmental samples are analysed for the presence of these particles. For this purpose, optical methods and spectroscopic methods are used. Fourier transform infrared (FTIR) spectroscopy is used to identify synthetic rubber, most likely derived from car tyres. A complementary confocal microscopy method is used to confirm the FTIR results. The soil samples and road dust from the areas with heavy traffic are tested. An average of 372 ± 50 fragments per kilogram dry weight are detected in the soil samples. In the case of samples from the road, this number is 515 ± 20 fragments per kilogram of dry matter. In the samples, most of the microplastics come from tyres, which confirms the scientists’ assumptions about the amount of emissions in the environment. More than 90% of the black fragments later identified as tyre-derived synthetic rubber are found in the samples. A greater number of microplastics are found in road dust samples than in the soil. This may be due to the direct influence of braking, which causes greater accumulation of samples at the emission source than at a short distance into the soil. There is also a noticeable difference in the size of the fraction. In the case of soils, a fraction below 50 µm accounts for the majority of cases. When one analyses road dust samples, one may observe that most of the fractions are between 50 and 200 µm. This may be due to the possibility of smaller emission particles over longer distances and the greater degradation process that occurs in soils. The microplastics from the road dust are less degraded than the microplastics from the soil.

Evaluation of life expectancy loss associated with submicron and fine particulate matter (PM1 and PM2.5) air pollution in Nanjing, China

Particulate matters with an aerodynamic diameter ≤1 μm (PM₁) significantly increased mortality risk, and the effect of PM₁ was even greater than that of PM_2.5 (aerodynamic diameter ≤2.5 μm). But the quantitative impact of PM₁ on life expectancy was unknown. We aim to examine the extent to which that people's life expectancy was shortened by PM₁ and PM_2.5. We obtained daily data on deaths, PM₁ and PM_2.5 records, and weather variables during 2016-2017 in Nanjing, China. Years of life lost (YLLs) were calculated by matching each decedent's age and sex to the Chinese life table. The fitted nonlinear dose-response associations of YLLs with PM₁ and PM_2.5 were estimated by utilizing a generalized additive model with a Gaussian link that controlled for confounding factors including meteorological variables, day of week, and long-term trend and seasonality. The effect estimates were presented as the YLLs when PM₁ and PM_2.5 concentrations fell in different ranges. Life expectancy losses attributable to PM₁ and PM_2.5 were calculated. Stratified analyses were also performed by age, sex, and death causes. Significant PM-YLL associations were observed, with greater increases in YLLs associated with PM₁ (68.9 thousand). PM₁ was estimated to reduce life expectancy, which was greater than PM_2.5 (PM₁: 1.67 years; PM_2.5: 1.55 years). For PM₁, greater years of loss in PM-related life expectancy were found in the female group, ≥65 years group, and cardiovascular disease group. Exposure to PM₁ had a greater impact on life expectancy loss than did PM_2.5. Constant efforts are urgently needed to control PM₁ air pollution to improve people's longevity.

Global burden of COPD attributable to ambient PM2.5 in 204 countries and territories, 1990 to 2019: A systematic analysis for the Global Burden of Disease Study 2019

The global spatiotemporal pattern of the COPD burden attributable to ambient PM2.5 is unknown in the context of the continuing increase in exposure to ambient PM2.5. Data on COPD burden attributable to ambient PM2.5 from 1990 to 2019 were retrieved from the Global Burden of Disease Study 2019. Cases and age-standardized rates of COPD mortality (ASMR) and disability-adjusted life years (ASDR) were estimated by age, sex, region, and country. The estimated annual percentage change (EAPC) was calculated to quantify the secular trends of ASMR and ASDR from 1990 to 2019. Globally, the number of COPD deaths and DALYs attributable to ambient PM2.5 both increased by over 90% from 1990 to 2019, but ASMR and ASDR both slightly decreased, with EAPC of -0.58 (95% CI: -0.72, -0.44) and -0.40 (95% CI: -0.51, -0.29), respectively. Most COPD deaths and DALYs attributable to PM2.5 occurred in the middle sociodemographic index (SDI) region, but the fastest growth of ASMR and ASDR occurred in the low SDI region, with EAPCs of 2.41 (95% CI: 2.23, 2.59) and 2.34 (95% CI: 2.16, 2.52), respectively. East Asia and South Asia were the high-risk areas of COPD deaths and DALYs attributable to PM2.5, among which China and India were the countries with the heaviest burden. COPD deaths and DALYs attributable to PM2.5 mainly occurred in individuals 70-89 years old and 60-84 years old, respectively. The age-specific rates of mortality and DALYs had a rapid increase in low and low-middle SDI regions from 1990 to 2019. The ASMR or ASDR had a reverse V-shaped relationship with SDI. In summary, the ambient PM2.5-attributable COPD burden is socioeconomic- and age-dependent, and it mediates the heterogeneity of spatial and temporal distribution. Low- and middle-income countries endure the highest ambient PM2.5-attributable COPD burden due to the high exposure to PM2.5 and poor availability and affordability of medicines and diagnostic tests.

Fine particulate matter exposure exacerbated nasal mucosal damage in allergic rhinitis mice via NLRP3 mediated pyroptosis

BACKGROUND

The incidence of nasal allergy/allergic rhinitis (AR) is rising worldwide, which has become a serious public health problem. Epidemiological studies point that exposure to environmental PM2.5 is closely linked to AR aggravation, however, the exactly mechanism is not clear. This study was performed to reveal molecular mechanisms of PM2.5 -induced AR deterioration.

METHODS

Morphology and element analysis of PM2.5 was examined by scanning electron microscopy (SEM) and Energy Dispersive Spectrometer (EDS). A total of 24 female C57BL/6 mice were divided into three groups (control group, AR group, and PM2.5 + AR group, each group contains 8 mice). Mice from AR group and PM2.5 + AR group were intraperitoneally injected with OVA suspension (0.004% OVA+3% aluminum hydroxide) on days 1, 7, and 14. 0.2 mL /kg B.W. for sensitization; then the same mice were intranasal instilled with 5% OVA solution daily for 7 days to established AR mice model (each nostril for 10 μl, day 15-21). The mice were intranasal instilled PBS (control group and AR group, each nostril for 10 μl) or PM2.5 (AR + PM2.5 group, 4.0 mg/kg b.w., each nostril for 10 μl) at the same way from day 23-29. The nasal symptoms were evaluated after the last instillation of PM2.5. Pathological changes and ultrastructure of nasal mucosa were observed by HE staining and SEM. Goblet cells hyperplasia was performed by Periodic acid-Schiff (PAS) staining. NLRP3, Caspase-1, GSDMD and IL-1β protein expression were assessed by immunohistochemical (IHC) staining.

RESULTS

Exposure to PM2.5 aggravated rhinitis symptom, promoted the secretion of serum IgE level and destroyed ultrastructural of nasal mucosa. Interestingly, NLRP3, Caspase-1 GSDMD and IL-1β protein expression were obviously elevated. NLRP3 /Capase-1/ GSDMD meditated cell pyroptosis participated in the process of AR exacerbation. However, macrophage is not the main effector cell.

CONCLUSION

PM2.5 exposure induces aggravation of allergic rhinitis, which is related to NLRP3 inflammasome meditated caspase-1 activation and cell pyroptosis in nasal mucosal.

Changes in Air Pollution-Related Behaviour Measured by Google Trends Search Volume Index in Response to Reported Air Quality in Poland

Decreased air quality is connected to an increase in daily mortality rates. Thus, people’s behavioural response to sometimes elevated air pollution levels is vital. We aimed to analyse spatial and seasonal changes in air pollution-related information-seeking behaviour in response to nationwide reported air quality in Poland. Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM₁₀ and PM_2.5 concentrations measured across Poland between 2016 and 2019 as well as locations of monitoring stations were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation Coefficients were used to measure the strength of spatial and seasonal relationships between reported air pollution levels and the popularity of search queries. The highest PM₁₀ and PM_2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air pollution-related keywords. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels. It appears that Poles are socially aware of this issue and that their intensification of the information-seeking behaviour seems to indicate a relevant ad hoc response to variable threat severity levels.

Comparison of PM10 Sources at Traffic and Urban Background Sites Based on Elemental, Chemical and Isotopic Composition: Case Study from Krakow, Southern Poland

In large urban agglomerations, car traffic is one of the main sources of particulate matter. It consists of particulate matter directly generated in the process of incomplete liquid fuel burning in vehicle engine, secondary aerosols formed from exhaust gaseous pollutants (NOx, SO2) as well as products of tires, brake pads and pavement abrasion. Krakow is one of the cities in Europe with the highest concentrations of particulate matter. The article presents the results of combined elemental, chemical and isotopic analyses of particulate matter PM10 at two contrasting urban environments during winter and summer seasons. Daily PM10 samples were collected during the summer and winter seasons of 2018/2019 at two stations belonging to the network monitoring air quality in the city. Mean PM10 concentrations at traffic-dominated stations were equal to 35 ± 7 µg/m3 and 76 ± 28 µg/m3 in summer and winter, respectively, to be compared with 25.6 ± 5.7 µg/m3 and 51 ± 25 µg/m3 in summer and winter, respectively, recorded at the urban background station. The source attribution of analyzed PM10 samples was carried out using two modeling approaches: (i) The Positive Matrix Factorization (PMF) method for elemental and chemical composition (concentrations of elements, ions, as well as organic and elemental carbon in daily PM10 samples), and (ii) Isotope Mass Balance (IMB) for 13C and 14C carbon isotope composition of carbonaceous fraction of PM10. For PMF application, five sources of particulate matter were identified for each station: fossil fuel combustion, secondary inorganic aerosols, traffic exhaust, soil, and the fifth source which included road dust, industry, construction work. The IMB method allowed the partitioning of the total carbon reservoir of PM10 into carbon originating from coal combustion, from biogenic sources (natural emissions and biomass burning) and from traffic. Both apportionment methods were applied together for the first time in the Krakow agglomeration and they gave consistent results.

Fine Particulate Matter-Induced Oxidative Stress Mediated by UVA-Visible Light Leads to Keratinocyte Damage

The human skin is exposed to various environmental factors including solar radiation and ambient air pollutants. Although, due to its physical and biological properties, the skin efficiently protects the body against the harm of environmental factors, their excessive levels and possible synergistic action may lead to harmful effects. Among particulate matter present in ambient air pollutants, PM2.5 is of particular importance for it can penetrate both disrupted and intact skin, causing adverse effects to skin tissue. Although certain components of PM2.5 can exhibit photochemical activity, only a limited amount of data regarding the interaction of PM2.5 with light and its effect on skin tissue are available. This study focused on light-induced toxicity in cultured human keratinocytes, which was mediated by PM2.5 obtained in different seasons. Dynamic Light Scattering (DLS) and Atomic Force Microscopy (AFM) were employed to determine sizes of the particles. The ability of PM2.5 to photogenerate free radicals and singlet oxygen was studied using EPR spin-trapping and time-resolved singlet oxygen phosphorescence, respectively. Solar simulator with selected filters was used as light source for cell treatment to model environmental lightning conditions. Cytotoxicity of photoexcited PM2.5 was analyzed using MTT assay, PI staining and flow cytometry, and the apoptotic pathway was further examined using Caspase-3/7 assay and RT-PCR. Iodometric assay and JC-10 assay were used to investigate damage to cell lipids and mitochondria. Light-excited PM2.5 were found to generate free radicals and singlet oxygen in season-dependent manner. HaCaT cells containing PM2.5 and irradiated with UV-Vis exhibited oxidative stress features-increased peroxidation of intracellular lipids, decrease of mitochondrial membrane potential, enhanced expression of oxidative stress related genes and apoptotic cell death. The data indicate that sunlight can significantly increase PM2.5-mediated toxicity in skin cells.

Origin, distribution, and perspective health benefits of particulate matter in the air of underground salt mine: a case study from Bochnia, Poland

The composition and distribution of airborne particles in different locations in a salt mine were determined in terms of their origin, the distance from the air inlet, and the adaptation of post-mining chambers and corridors for tourists and general audience. The composition of aerosols in air was also evaluated from the perspective of human health. Air samples were collected on filters by using portable air pumps, in a historical underground salt mine in Bochnia (Poland), which is currently a touristic and recreation attraction and sanatorium. The particulate matter (PM) concentration was determined using the gravimetric method by weighing quartz filters. The content of carbon, water-soluble constituents, trace elements, and minerals was also determined. A genetic classification of the suspended matter was proposed and comprised three groups: geogenic (fragments of rock salt and associated minerals from the deposit), anthropogenic (carbon-bearing particles from tourist traffic and small amounts of fly ash, soot, and rust), and biogenic particles (occasional pollen). The total PM concentration in air varied between 21 and 79 μg/m³ (with PM₄ constituting 4-24 μg/m³). The amount of atmospheric dust components coming from the surface was low and decreased with the distance from the intake shaft, thus indicating the self-cleaning process. NaCl dominated the water-soluble constituents, while Fe, Al, Ag, Mn, and Zn dominated the trace elements, with the concentration of majority of them below 30 ng/m³. These metals are released into air from both natural sources and the wear or/and corrosion of mining and tourists facilities in the underground functional space. No potentially toxic elements or constituents were detected. The presence of salt particles and salty spray in the atmosphere of salt mine, which may have anti-inflammatory and antiallergic properties, is beneficial to human health. This study will allow for a broader look at the potential of halotherapy in underground salt mines from a medical and regulatory point of view.

Assessment of occupational exposure to diesel particulate matter through evaluation of 1-nitropyrene and 1-aminopyrene in surface coal miners, India

DPM (diesel particulate matter) is ubiquitously present in the mining environment and is known for mutagenicity and carcinogenicity to humans. However, its health effects in surface coal mines are not well studied, particularly in India. In this study, DPM exposure and corresponding exposure biomarkers were investigated in four different surface coal mines in Central India. To document and evaluate the DPM exposure in surface coal miners, we characterized 1-NP (1-nitropyrene) in the mining environment as surrogate for DPM using Sioutas Cascade Impactor. Exposure biomarkers were analyzed by collecting post work shift (8-h work shift) urine samples and determining the concentrations of 1-aminopyrene (1-AP) as a metabolite of 1-NP and 8-hydroxydeoxyguanosine (8OHdG) as DNA damage marker. We observed high concentration of 1-NP (7.13-52.46 ng/m³) in all the mines compared with the earlier reported values. The average creatinine corrected 1-AP and 8OHdG levels ranged 0.07-0.43 [Formula: see text]g/g and 32.47-64.16 [Formula: see text]g/g, respectively, in different mines. We found 1-AP in majority of the mine workers' urine (55.53%) and its level was higher than that reported for general environmental exposure in earlier studies. Thus, the study finding indicates occupational exposure to DPM in all the four mines. However, the association between 1-NP level and exposure biomarkers (1-AP and 8OHdG) was inconsistent, which may be due to individual physiological variations. The data on exposure levels in this study will help to understand the epidemiological risk assessment of DPM in surface coal miners. Further biomonitoring and cohort study are needed to exactly quantify the occupational health impacts caused by DPM among coal miners.

Early-life exposure to submicron particulate air pollution in relation to asthma development in Chinese preschool children

BACKGROUND

Emerging research suggested an association of early-life particulate air pollution exposure with development of asthma in childhood. However, the potentially differential effects of submicron particulate matter (PM; PM with aerodynamic diameter ≤1 μm [PM₁]) remain largely unknown.

OBJECTIVE

This study primarily aimed to investigate associations of childhood asthma and wheezing with in utero and first-year exposures to size-specific particles.

METHODS

We conducted a large cross-sectional survey among 5788 preschool children aged 3 to 5 years in central China. In utero and first-year exposures to ambient PM₁, PM with aerodynamic diameter less than or equal to 2.5 μm, and PM with aerodynamic diameter less than or equal to 10 μm at 1 × 1-km resolution were assessed using machine learning-based spatiotemporal models. A time-to-event analysis was performed to examine associations between residential PM exposures and childhood onset of asthma and wheezing.

RESULTS

Early-life size-specific PM exposures, particularly during pregnancy, were significantly associated with increased risk of asthma, whereas no evident PM-wheezing associations were observed. Each 10-μg/m³ increase in in utero and first-year PM₁ exposure was accordingly associated with an asthma's hazard ratio in childhood of 1.618 (95% CI, 1.159-2.258; P = .005) and 1.543 (0.822-2.896; P = .177). Subgroup analyses suggest that short breast-feeding duration may aggravate PM-associated risk of childhood asthma. Each 10-μg/m³ increase in in utero exposure to PM₁, for instance, was associated with a hazard ratio of 2.260 (1.393-3.666) among children with 0 to 5 months' breast-feeding and 1.156 (0.721-1.853) among those longer breast-fed.

CONCLUSIONS

Our study added comparative evidence for increased risk of childhood asthma in relation to early-life PM exposures, highlighting stronger associations with ambient PM₁ than with PM with aerodynamic diameter less than or equal to 2.5 μm and PM with aerodynamic diameter less than or equal to 10 μm.

Individual effects of trichomes and leaf morphology on PM2.5 dry deposition velocity: A variable-control approach using species from the same family or genus

Urban green infrastructure is closely linked to the alleviation of pollution from atmospheric particulate matter. Although particle deposition has been shown to depend on leaf characteristics, the findings from earlier studies are sometimes ambiguous due to the lack of controlling variables. In this study, we investigated the impact of leaf morphological characteristics on PM_2.5 dry deposition velocity by employing a control-variable approach. We focused on four indices: trichome density, petiole length, aspect ratio (width-to-length ratio), and fractal deviation. For each index, tree species were chosen from the same family or genus to minimize the influence of other factors and make a group of treatments for an individual index. The dry deposition velocities of PM_2.5 were determined through application of an indirect method. The results revealed that the presence of leaf trichomes had a positive effect on PM_2.5 dry deposition velocity, and a higher trichome density also led to a greater particle deposition velocity. Lower leaf aspect ratio, shorter petioles, and higher leaf fractal deviation were associated with greater PM_2.5 dry deposition velocity. The control-variable approach allows to investigate the correlation between deposition velocity and a certain leaf characteristic independently while minimizing the effects of others. Thus, our study can clarify how a single leaf characteristic affects particle deposition velocity, and expound its potential mechanism more scientifically than the published studies. Our research points out the importance of controlling variables, and also provides ideas for future researches on related factors to be found. Meanwhile the results would help provide insight into design improvements or adaptive management for the alleviation of air pollution.

Particulate air pollution and respiratory Haemophilus influenzae infection in Mianyang, southwest China

Particulate air pollution is correlated with many respiratory diseases. However, few studies have focused on the relationship between air particulate exposure and respiratory Heamophilus influenzae infection. Therefore, we detected respiratory Heamophilus influenzae infection by bacterial culture of sputum of patients, and we collected particulate air pollution data (including PM2.5 and PM10) from a national real-time urban air quality platform to analyze the relationship between particulate air pollution and respiratory Heamophilus influenzae infection. The mean concentrations of PM2.5 and PM10 were 37.58 μg/m3 and 58.44 μg/m3, respectively, showing particulate air pollution remains a severe issue in Mianyang. A total of 828 strains of Heamophilus influenzae were detected in sputum by bacterial culture. Multiple correspondence analysis suggested the heaviest particulate air pollution and the highest Heamophilus influenzae infection rates were all in winter, while the lowest particulate air pollution and the lowest Heamophilus influenzae infection rates were all in summer. In a single-pollutant model, each elevation of 10 μg/m3 of PM2.5, PM10, and PM2.5/10 (combined exposure level) increased the risk of respiratory Heamophilus influenzae infection by 34%, 23%, and 29%, respectively. Additionally, in the multiple-pollutant model, only PM2.5 was significantly associated with respiratory Heamophilus influenzae infection (B, 0.46; 95% confidence interval, 0.05-0.87), showing PM2.5 is an independent risk factor for respiratory Heamophilus influenzae infection. In summary, this study highlights air particulate exposure could increase the risk of respiratory Heamophilus influenzae infection, implying that stronger measures need to be taken to protect against respiratory infection induced by particulate air pollution.

Chemical characterization and source apportionment of PM1 and PM2.5 in Tianjin, China: Impacts of biomass burning and primary biogenic sources

The submicron particulate matter (PM₁) and fine particulate matter (PM_2.5) are very important due to their greater adverse impacts on the natural environment and human health. In this study, the daily PM₁ and PM_2.5 samples were collected during early summer 2018 at a sub-urban site in the urban-industrial port city of Tianjin, China. The collected samples were analyzed for the carbonaceous fractions, inorganic ions, elemental species, and specific marker sugar species. The chemical characterization of PM₁ and PM_2.5 was based on their concentrations, compositions, and characteristic ratios (PM₁/PM_2.5, AE/CE, NO₃^-/SO₄^2-, OC/EC, SOC/OC, OM/TCA, K+/EC, levoglucosan/K⁺, V/Cu, and V/Ni). The average concentrations of PM₁ and PM_2.5 were 32.4 µg/m³ and 53.3 µg/m³, and PM₁ constituted 63% of PM_2.5 on average. The source apportionment of PM₁ and PM_2.5 by positive matrix factorization (PMF) model indicated the main sources of secondary aerosols (25% and 34%), biomass burning (17% and 20%), traffic emission (20% and 14%), and coal combustion (17% and 14%). The biomass burning factor involved agricultural fertilization and waste incineration. The biomass burning and primary biogenic contributions were determined by specific marker sugar species. The anthropogenic sources (combustion, secondary particle formation, etc) contributed significantly to PM₁ and PM_2.5, and the natural sources were more evident in PM_2.5. This work significantly contributes to the chemical characterization and source apportionment of PM₁ and PM_2.5 in near-port cities influenced by the diverse sources.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

Complex Characterization of Fine Fraction and Source Contribution to PM2.5 Mass at an Urban Area in Central Europe

It is well documented that Southern Poland is one of the most polluted areas in Europe due to the highest airborne concentrations of particulate matter (PM). Concentrations of fine particles are especially high in winter. Apart from detailed number concentrations, it is essential to accurately identify and quantify specific particulate pollution sources. Only a few Polish research centers are involved in such experiments—among them is Krakow research group. For the most part, research focuses on collecting 24-h average samples from stationary PM samplers at ambient monitoring sites and quantifying the specific elements and chemical constituents in PM. This approach includes modeling methods that can use the variability in physical and chemical PM characteristics as an input dataset to identify possible sources of the particles. The objective of this paper is to provide research results based on data collected from June 2018 to May 2019 from a single monitoring station at a central urban site. Careful comparison of data obtained prior to a 2019 law prohibiting solid fuel burning in the city of Krakow with data (2019–2020) when a regulation went into effect should indicate progress by noting lower PM levels. This work has shown that the method applied and Krakow results might be of interest to the broader community in regions of high PM concentration.

Effects of the leaf functional traits of coniferous and broadleaved trees in subtropical monsoon regions on PM2.5 dry deposition velocities

Plants can intercept airborne particulate matter through deposition. Different types of plants exhibit different functional leaf traits, which can affect the dry deposition velocity (V_d). However, the most crucial leaf traits of coniferous and broadleaved trees remain unidentified. In this study, we selected 18 typical plants from the subtropical monsoon regions, where PM_2.5 (fine particulate matter with a diameter of ≤2.5 μm) concentrations are relatively high, and classified them into coniferous and broadleaved categories. Subsequently, we analyzed the relationships between V_d and leaf surface free energy (SFE), single leaf area (LA_s), surface roughness (SR), specific leaf area (SLA), epicuticular wax content (EWC), and width-to-length ratio (W/L). The results indicated that most coniferous trees exhibited a high V_d. The correlation analysis revealed that SFE, SR, LA_s, and W/L were the key factors that affected the V_d of all the tested species. SFE and SLA had the strongest influence on the V_d of broadleaved trees, whereas LA_s and SLA had the strongest effect on that of coniferous trees. Most coniferous trees had a high SLA, which can reduce water loss and hinder particle deposition. However, the stiff leaves of coniferous trees fluttered less, resulting in a larger leaf area that enhanced the capture efficiency. The leaf structure of broadleaved trees is more flexible, resulting in erratic flutter, which may impede deposition and lead to high resuspension. Coniferous and broadleaved trees may have different dominant leaf traits that affect particle deposition.

Ambient air pollution and its influence on human health and welfare: an overview

Human health is closely related to his environment. The influence of exposure to air pollutants on human health and well-being has been an interesting subject and gained much volume of research over the last 50 years. In general, polluted air is considered one of the major factors leading to many diseases such as cardiovascular and respiratory disease and lung cancer for the people. Besides, air pollution adversely affects the animals and deteriorates the plant environment. The overarching objective of this review is to explore the previous researches regarding the causes and sources of air pollution, how to control it and its detrimental effects on human health. The definition of air pollution and its sources were introduced extensively. Major air pollutants and their noxious effects were detailed. Detrimental impacts of air pollution on human health and well-being were also presented.

Coagulation effect of aero submicron particles on plant leaves: Measuring methods and potential mechanisms

Aero submicron particles (d < 1 μm) have attracted widely attention due to their difficulty in removal from the air and serious threat to human health. Leaves are considered as important organs to purify particulate matter and alleviate air pollution. However, the current research mainly focuses on the removal capacity of particulate matter by urban plants at different scales, there are relatively few studies on the change of particle diameter at the air-leaf interface during this process. This study is one of the first to propose the existence of coagulation effect of aero submicron particles on the leaves, and a sweep-resuspension method and X-ray microscope were used to measure such size changes of two typical subtropical broad-leaf plants. The results showed that the size of submicron particles increased significantly during the migration from atmosphere to leaf surface: the average particle size increased from 0.48 μm at emission to 3.40 μm on the leaf surface, while the proportion of submicron particles decreased from 95% to less than 20%. The sweep-resuspension method was easy to implement, the data was easy to obtain, and the cost was low, therefore it could be widely used in the determination of the coagulation effect. The coagulation effect was also inferred as an important mechanism used by plants to reduce particulate matter. In the process of particulate removal: coagulation effect and dry deposition are actually two steps that occur simultaneously and interact. This finding refined the understanding of particulate removal processing, and laid a foundation for further research on factors affecting coagulation, which can be helpful for optimizing tree species selection and plant arrangement.

Influence of Individual Household Heating on PM2.5 Concentration in a Rural Settlement

This article reports the results of research on the concentration of particulate matter (PM) in two places in one village named Kotórz Mały (Poland). The main point of the research was to check the influence scale of different low-emission source forms as components of the anthropogenic factor driving the changes in local air quality. Measurements were made over five cold seasons. To investigate the dust concentrations, the gravimetric and optical method was used. The weather conditions were measured with portable weather stations. It was found that the character of individual heating systems had a major influence on local air quality. The presence of a permanent state of the troposphere and temperature inversion led to the inhibition of pollution dispersion processes and significant local changes, exceeding the recommended PM2.5 concentrations limit. The effects of policy still don’t influence air quality trends in the Polish village. The main problem of high concentrations of PM2.5 is the old generation of individual heating systems and the lack of significant support from local and national authorities. For the terms considered and the period of observation, meteorological measurements can be considered a sufficient foundation for the estimation of the occurrence of worrying conditions.

Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution

Characteristics of the spatial and temporal distribution of air pollutants may reveal the cause of air pollution, especially for large regions where the anthropogenic pollutant emission is concentrated. This study addresses this issue by focusing on Shandong province, which has the highest air pollutant emissions in China. First, the spatial and temporal variation characteristics of the observed concentrations of conventional pollutants are analyzed in detail. The most prominent indicator of the problem (PM_2.5), was selected as the key analytical object. On the spatial scale, the Multivariate Moran model was used to identify factors affecting the spatial distribution of PM_2.5. On the time scale, wavelet analysis was used to explore the fluctuation characteristics of PM_2.5 at different time periods. Results show that there are significant regional differences in pollutant concentration within Shandong province. The concentration of particulate matter and gaseous pollutants in western and northern Shandong is significantly higher than eastern Shandong. The average concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ were highest in winter and lowest in summer, whereas concentration of O₃ peaked in summer. For PM_2.5, the annual mean concentration has a significant spatial correlation with SO₂ emission, GDP per capita, population density and energy consumption per unit of GDP; in addition, the correlation between different regions and various indices is different. On the time scale, the fluctuation energy of PM_2.5 concentrated in Dezhou and Liaocheng is the strongest on December 18 and 19, 2015. The inversion temperature has a strong influence on the daily variation of PM_2.5 concentration. The formation and evolution of atmospheric pollution, therefore, can be explored by combining the temporal and spatial distribution of pollutants, providing a comprehensive analytical method for atmospheric pollution in different regions.

The influence of local emissions and regional air pollution transport on a European air pollution hot spot

The EU air quality standards have been frequently exceeded in one of the European air pollution hot spots: Ostrava. The aim of this study was to perform an air quality comparison between an urban site (Radvanice), which has a nearby metallurgical complex, and a suburban site (Plesná) to estimate air pollution sources and determine their local and/or regional origins. Twenty-four hour PM₁ and PM₁₀ (particular matter) concentrations, detailed mass size distributions (MSDs) to distinguish the sources of the fine and coarse PM, and their chemical compositions were investigated in parallel at both sites during the winter of 2014. Positive matrix factorization (PMF) was applied to the PM₁ and PM₁₀ chemical compositions to investigate their sources. During the measurement campaign, prevailing northeastern-southwestern (NE-SW) wind directions (WDs) were recorded. Higher average PM₁₀ concentration was measured in Radvanice than in Plesná, whereas PM₁ concentrations were similar at both sites. A source apportionment analysis revealed six and five sources for PM₁₀ and PM₁, respectively. In Radvanice, the amount of PM and the most chemical species were similar under SW and NE WD conditions. The dominant sources were industrial (43% for PM₁₀ and 27% for PM₁), which were caused by a large metallurgical complex located to the SW, and biomass burning (25% for PM₁₀ and 36% for PM₁). In Plesná, the concentrations of PM and all species significantly increased under NE WD conditions. Secondary inorganic aerosols were dominant, with the highest contributions deriving from the NE WD. Therefore, regional pollution transport from the industrial sector in Silesian Province (Poland) was evident. Biomass burning contributed 22% and 24% to PM₁₀ and PM₁, respectively. The air quality in Ostrava was influenced by local sources and regional pollution transport. The issue of poor air quality in this region is complex. Therefore, international cooperation from both states (the Czech Republic and Poland) is needed to achieve a reduction in air pollution levels.